# -*- coding: utf-8 -*-
from datetime import timedelta
from utils.operators.spark_submit import SparkSubmitOperator
from jms_dm_bi_day.depend.ods_depend import jms_ods__tab_report_errorseparatedetail
from jms_dm_bi_day.depend.ods_depend import jms_ods__ass_scan_small_upper

# from ..dm_waybill_prescription_reach_details import jms_dm__dm_waybill_prescription_reach_details_dt

jms_dm__dm_center_sort_count_dt = SparkSubmitOperator(
    task_id='jms_dm__dm_center_sort_count_dt',
    email=['guoruiling@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_center_sort_count_dt_{{ execution_date | date_add(1) | cst_ds }}',
    pool_slots=4,
    # sla=timedelta(hours=7),
    driver_memory='2G',
    executor_memory='5G',
    executor_cores=10,
    num_executors=4,
    conf={'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
          'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
          'spark.dynamicAllocation.maxExecutors': 12,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
          'spark.sql.sources.partitionOverwriteMode': 'dynamic',  # 允许删改已存在的分区
          'spark.executor.memoryOverhead': '1G',  # 堆外内存
          'spark.default.parallelism': 600,
          'spark.sql.shuffle.partitions': 600
          },
    jars='hdfs:///scheduler/jms/spark/grl/dm_center_sort_count_dt/common-1.0-SNAPSHOT.jar',  # 依赖 jar 包
    java_class='com.yunlu.bigdata.jobs.export.ExportCenterSortCountData',  # spark 主类
    application='hdfs:///scheduler/jms/spark/grl/dm_center_sort_count_dt/original-jobs-1.0-SNAPSHOT.jar',
    # spark jar 包
    application_args=['{{ execution_date | cst_ds }}'],
    #execution_timeout=timedelta(hours=1)
    #excel平均时长:5分15秒
    #execution_timeout = timedelta(minutes=15)
    #excel平均时长:5分15秒
    execution_timeout = timedelta(minutes=30),
)
jms_dm__dm_center_sort_count_dt << [
    jms_ods__ass_scan_small_upper,
    jms_ods__tab_report_errorseparatedetail
]
